Abstract

Absolute attitude estimation sensors provide high accuracy pointing capabilities to spacecraft, but as developed thus far, they constitute a large fraction of CubeSat mission's budget. We introduce SPE Lab Open Star Tracker (SOST), an ultra-low-cost solution that currently provides sub-arcminute precision at a frequency of 1 to 3 estimations per minute in the Lost-In-Space scenario. Our Star Tracker development rests on open source astronomy software, the Raspberry Pi 3 B+, and its camera. We developed a new algorithm to solve the Lost-In-Space problem that works by acquiring an image and comparing it with different stellar catalog segments. We tested our algorithm using images from working satellites. The functioning of our platform was evaluated by using night-sky pictures taken from ground. We also conducted environmental tests of our platform by using a thermal-vacuum chamber. We optimized the catalog segment separation by analyzing the execution time, success rate, precision, and power consumption of the full platform. SOST delivers a mean precision below 1-arcminute for the boresight direction. With a segment separation of 10 degrees, the attitude estimation is found in the 97.3% of the cases with processing time under 20s. The success rate improves to 99.8% by using 5 degrees as segments separation but processing time doubles. This platform is open and freely available to CubeSat researchers interested in further development or deployment.